Jim Andreas

Visualization of molecules on Android systems

[Jim Andreas @jim__andreas]

@mercoglianos the model is trending toward the "yellow fleet"

[Jim Andreas @jim__andreas]

@HedgieMarkets hint: there is ZERO inflation on stuff that you refuse to buy!!!

[Dave Collum @DavidBCollum]

This is very funny...

cc @JG_Nuke

https://t.co/DLclMelQwD

[Bart Mol @Bart_Mol]

Me explaining AI to friends

[Jim Andreas @jim__andreas]

@Chartfest1 $SPX p/e in 1982 was 7.7 in jan, says google...

[Jim Andreas @jim__andreas]

@DavidBCollum Please be careful here - and BE-FAST!! (not kidding around here) :

[Jim Andreas @jim__andreas]

@MauiBoyMacro Nice work on the x axis - you have clearly been planning ahead...

[Jim Andreas @jim__andreas]

Hmm a new factoid: Gemini: Garish magenta is an intense, non-spectral color (Hex #FF00FF) created by blending red and violet light. Because it falls outside the visible light spectrum, the human eye perceives it as aggressively vibrant. It is frequently used in bold design, high-contrast art, and retrofuturistic or cyberpunk aesthetics.

[Jim Andreas @jim__andreas]

A most interesting conversation!! Zulauf and Gundlach *together* and *mostly* agreeing with each other...

[John E. Montana @JohnEMontana]

.@TruthGundlach nails today's core economic risk: Private credit is a shadow bubble constructed on systemic dishonesty about true credit quality & illusory liquidity dressed up in fractional reserves. Offshore reinsurance chains are papering over the rot. Unlike 2008, when the ABX index was broadcasting distress in real time, there's no ticker for this. Reality stays concealed until it's forced & when the forcing event arrives, it will hit insurers, pension funds & markets with no warning & no exit. JG "This is a problem wrapped up in an enigma with no solution." H/T @RudyHavenstein

[Arnaud Bertrand @RnaudBertrand]

This is a really fascinating paper that everyone interested in China's industrial policy should read.

It destroys so many myths (see below), and is written by deeply credible people who conducted over three years of fieldwork in China and interviewed 60+ Chinese officials, entrepreneurs, and engineers. When it comes to China studies, it literally doesn't get more rigorous than this.

First myth it destroys: contrary to popular belief, Beijing's industrial policy didn't build the companies that became China's EV champions. They rose largely **despite** it, through its cracks.

For sure, Beijing did favor EVs as an industry and pushed hard for it but their big bet was SOEs (State Owned Enterprises): research grants, pilot programs, licenses, cheap credit - virtually all of it flowed to state firms.

The result? China's actual EV champions - BYD, Geely, NIO, XPeng, Li Auto, etc. - are overwhelmingly private firms that succeeded despite Beijing favoring their SOE competitors.

How so? Because, when favoring SOEs, the central government didn't just pick winning companies, it picked winning cities, each SOE being anchored in a specific city: Shanghai (SAIC), Changchun (FAW), Wuhan-Shiyan (Dongfeng), etc.

Which means that every city not on the list, that wanted a piece of the auto boom, had only one option left: team up with private entrepreneurs who were equally excluded from central government favor.

That's what truly fueled China's EV miracle: an alliance of the excluded, between local private entrepreneurs and local mayors.

This is the biggest misconception this paper destroys: the reality is that the "Chinese state capitalism" that many in the West think powered the EV boom actually tried to block many of these companies from existing. In effect, it was closer to an obstacle course that local actors (mayors and provinces) learned to game.

Geely - now the third largest automaker in China - is a fantastic example of this.

First of all, it started off illegal since, to build passenger cars, you had to have a central government license and they couldn't get one. Zhejiang Province told them to go ahead regardless because the province had hundreds of auto parts suppliers but no carmaker of its own.

It's only a couple of years later, recognizing the fait-accompli that Geely was producing cars and was competitive, that the central government admitted them to the National Sedan Catalog - effectively legalizing them retroactively because there were facts on the ground.

Then there was the Volvo acquisition in 2010, which is fair to say - looking back - proved to be the most strategically valuable acquisition in Chinese automotive history. Despite it being presented at the time (and still described this way today) as "China buying Volvo", all 3 major state-backed banks in China (Export-Import Bank, China Development Bank, Bank of China) refused to finance the deal. The only state-bank money Geely managed to get was a $200 million loan from a provincial branch of China Construction Bank - a tiny fraction of what the deal required.

Geely actually did the deal with Goldman Sachs money via Hong Kong plus loans and equity from four local governments (Chengdu, Zhangjiakou, Daqing, Shanghai's Jiading district), each of which bought in by securing a Volvo plant or headquarters for itself.

In effect, the doors that Beijing controlled were largely closed to Geely, but it made it because the doors subnational actors controlled were opened.

Which all means this paper destroys another very common myth: the big merit of the central government in all this was to be relatively chill about it, to NOT be dictatorial.

I just imagine if that had happened in France and you had - say - the mayor of Lyon or Marseilles open, fund and promote an unlicensed carmaker against Renault: the préfet would shut it down within weeks, and the mayor would be lucky to escape prosecution.

That's the irony: on industrial policy, the supposedly "totalitarian" Chinese state proved more tolerant of local defiance than most Western liberal democracies would be. Beijing's greatest contribution to the EV miracle wasn't the plan - it was looking the other way while the plan was being violated.

To be sure, the paper doesn't hide the costs of this system: ferocious local competition also produced what's known today in China as "involution" (内卷-Neijuan, basically a hypercompetitive price war), as well as some spectacular failures. For instance one county lost 6.6 billion yuan on a carmaker that never really made cars.

But that's precisely the point: this is a high-risk, high-reward model of decentralized experimentation, the very opposite of the careful central planning Westerners imagine.

I've repeated this countless times but it bears repeating again: the single greatest misconception people have about China is - probably because we wrongly associate communism with centralized control - that it is a monolith run from Beijing. Some even say it's run by "one man."

The reality is the exact opposite: China is, in practice, one of the most decentralized countries on earth. Roughly 85% of government spending in China happens at the subnational level - against about 30% in the average OECD country (and even less in France, which is actually one of the most centrally controlled countries on earth). A Chinese mayor commands fiscal resources, land, investment funds and policy latitude that virtually no Western mayor could dream of.

Last but not least, I'd be remiss not to mention what the paper has to say on the positive legacy of Mao and its role in the rise of EVs (given I myself wrote an article titled "Mao's economic record wasn't bad, actually": https://t.co/1NZgHqBHwg).

When it comes to China myths, none is more entrenched than the idea that Mao left behind nothing but ruins.

This paper confirms a key argument of my article: Mao's deliberate dispersal of industry across China (during the Great Leap Forward and Cultural Revolution decentralizations) left dozens of cities with their own small auto works. Inefficient, yes - but these scattered factories survived into the 1990s and became the seed stock of everything that followed: the industrial base, the engineers, and the production licenses that EV startups would use to enter the market.

The paper even says it outright: the fragmentation that industrial policy "sought to eradicate" is "precisely" what "ironically enabled" the EV sector's rapid rise.

This is exactly the mechanism I described in my Mao article: structures built in the Mao era - communes becoming township governments, commune enterprises becoming TVEs, Third Front factories seeding interior industrialization - became load-bearing foundations of the reform miracle.

Fittingly, the spark for China's first municipal carmaker adventure was literally a TVE (Township and Village Enterprise), the institutional descendants of Mao's commune enterprises: Tongbao, a kit-car maker in Wuhu whose success stunned local officials into building what became Chery (one of China's biggest carmakers today). You can't tell the story of China's EV miracle without crediting the legacy of Mao.

What's the biggest lesson in all this for Western policymakers?

The obvious one is that the part of industrial policy that most people assume China does and that they sometimes want to copy - i.e. the state picking winners - is actually the part that failed.

The part that did succeed is the China nobody in the West believes exists: a radically decentralized system with a high degree of tolerance for disobedience and experimentation.

We imagine China as a country where nothing happens without Beijing's approval when the reality is closer to the opposite: China's EV miracle happened precisely because localities asked for forgiveness rather than permission.

All in all, and this is the lesson I often come back to, this is yet another illustration of the importance of understanding China for what it is as opposed to the caricature we've built of it. This matters whichever "camp" you're in. If you see China as a rival, you can't compete with someone you don't understand. If you see them as a source of lessons, you can't emulate what you've misunderstood. Whatever you want from China - to compete with it or learn from it - the entry fee is the same: genuinely understanding it.

[Mo @atmoio]

Sam Altman is starting to panic

[Jim Andreas @jim__andreas]

@atmoio @grok is this video generated by ai or is this an actual presentation by a human?

[Jim Andreas @jim__andreas]

@HedgieMarkets Cf collosus the forbin project...

[lil Dove 🍁 @iAyushiRajput]

@historyinmemes A century later and these wrecks still look cooler than most functioning trains.
The desert doesnt forget. These rusting giants still stand as silent witnesses to Lawrence of Arabia greatest hits.

[Sir Escanor (𝘏𝘰𝘱𝘪𝘶𝘮 𝘚𝘭𝘢𝘺𝘦𝘳) @EscanorReloaded]

CEOs are quietly realizing the AI replacement plan has a problem.
Two problems, actually.

One: the token costs for running AI agents are now exceeding what they were paying the employees they fired.

Two: when the tokens run out, the AI stops. Just stops. No continuity. No workaround. Just a spinning wheel where your workforce used to be.

You fired humans to save money and bought a subscription that bills you into a corner.

The employees you let go knew what to do when things broke.
The AI just invoices you for the outage.

And then there’s the permission problem nobody wants to talk about.

To do its job, the AI agent needs access. Full access. Your systems, your patents, your contracts, your future plans. Everything you spent years building, handed over to a process that has no loyalty, no discretion, and no skin in the game.

You didn’t hire a replacement.
You gave a stranger with no soul the keys to everything you own.

Enjoy.

[Bull Theory @BullTheoryio]

🚨 THE ENTIRE AI BOOM MIGHT BE BUILT ON FAKE REVENUE.

Latest corporate filings show that OpenAI and Anthropic alone make up over half of the entire $2 trillion future cloud backlog held by Microsoft, Oracle, Google, and Amazon.

This massive pipeline is actually being created through a circular accounting trick called a round trip revenue loop.

But how it works ?

A tech giant gives billions of dollars to an AI startup as an "investment". But hidden in the contract is a strict rule forcing the startup to hand that exact same money straight back to the tech giant to rent their computer servers.

Look at the documented case of Microsoft and OpenAI.

When Microsoft invested $13 billion into OpenAI, it didn't just give them cash; it gave them "cloud credits" to use Microsoft servers. OpenAI used those exact credits to train its AI models, and Microsoft then turned around and recorded that server usage as brand new "cloud revenue" from a customer.

The tech giant is literally paying itself with its own money and calling it a sale.

This is why OpenAI’s annual cloud bill has ballooned to over $60 billion, double its actual revenue of $25 billion, kept alive solely by this recycled funding loop.

Anthropic runs the exact same play, spending $2.66 billion on Amazon Web Services in just nine months, which was basically 100% of all the money it earned at the time.

This manufactured demand triggers a second accounting trick where tech giants book massive paper profits. Every time a startup gets a higher value from a new funding round, the tech giant updates the value of its investment on its books and counts that unearned paper gain as direct profit.

In Q1 2026, Alphabet reported a record $62.6 billion profit, but $28.7 billion nearly half, was just a paper markup on its Anthropic investment. In the same quarter, Amazon reported $30.3 billion in profit, but $16.8 billion of it was just an Anthropic paper gain.

While Amazon reported record profits, its actual free cash flow collapsed 95% to just $1.2 billion because it had to spend $44.2 billion in real cash to build physical data centers.

This has created a massive danger where these giant companies rely heavily on just one or two unstable startups. Microsoft has 49% of its $627 billion future backlog tied to OpenAI, while Oracle has an incredible 54% of its entire $553 billion pipeline relying on OpenAI alone.

This perfectly mirrors the 2001 dot-com crash when Global Crossing and Qwest Communications swapped identical fiber-optic network capacity with each other just to book fake sales.

Qwest had to erase $1.4 billion in fake income, and Global Crossing went completely bankrupt.

The only difference is that the dot-com swaps were illegal, but today's AI loop is fully legal under current accounting rules.

This legal loop inflates tech company stock prices, forcing automatic retirement accounts and index funds to buy even more of these tech stocks. It is a self feeding loop where investments, sales, and stock prices all go up on paper without the AI technology ever making real cash profits.

[Jim Andreas @jim__andreas]

@DavidBCollum @NakedHedgie Yikes !!
At the end...

[Jeffrey Gundlach @TruthGundlach]

AI energy, materials and water needs might be the catalyst for the 4th turning kicking into high gear. Might turn out that human workers will be cheaper than AI, given resource limitations.

Imagine that!

[Jim Andreas @jim__andreas]

@DavidBCollum Gundlach has the best handle on the possible future, IMHO. Not only that, but he is also walking his talk...